diff --git a/Cargo.toml b/Cargo.toml
index dc725f01..f634f7ed 100644
--- a/Cargo.toml
+++ b/Cargo.toml
@@ -1,6 +1,6 @@
 [package]
 name = "nova-snark"
-version = "0.34.0"
+version = "0.35.0"
 authors = ["Srinath Setty <srinath@microsoft.com>"]
 edition = "2021"
 description = "High-speed recursive arguments from folding schemes"
diff --git a/examples/hashchain.rs b/examples/hashchain.rs
new file mode 100644
index 00000000..d0554568
--- /dev/null
+++ b/examples/hashchain.rs
@@ -0,0 +1,233 @@
+//! This example proves the knowledge of preimage to a hash chain tail, with a configurable number of elements per hash chain node.
+//! The output of each step tracks the current tail of the hash chain
+use bellpepper_core::{num::AllocatedNum, ConstraintSystem, SynthesisError};
+use ff::Field;
+use flate2::{write::ZlibEncoder, Compression};
+use generic_array::typenum::U24;
+use neptune::{
+  circuit2::Elt,
+  sponge::{
+    api::{IOPattern, SpongeAPI, SpongeOp},
+    circuit::SpongeCircuit,
+    vanilla::{Mode::Simplex, Sponge, SpongeTrait},
+  },
+  Strength,
+};
+use nova_snark::{
+  provider::{Bn256EngineKZG, GrumpkinEngine},
+  traits::{
+    circuit::{StepCircuit, TrivialCircuit},
+    snark::RelaxedR1CSSNARKTrait,
+    Engine, Group,
+  },
+  CompressedSNARK, PublicParams, RecursiveSNARK,
+};
+use std::time::Instant;
+
+type E1 = Bn256EngineKZG;
+type E2 = GrumpkinEngine;
+type EE1 = nova_snark::provider::hyperkzg::EvaluationEngine<E1>;
+type EE2 = nova_snark::provider::ipa_pc::EvaluationEngine<E2>;
+type S1 = nova_snark::spartan::snark::RelaxedR1CSSNARK<E1, EE1>; // non-preprocessing SNARK
+type S2 = nova_snark::spartan::snark::RelaxedR1CSSNARK<E2, EE2>; // non-preprocessing SNARK
+
+#[derive(Clone, Debug)]
+struct HashChainCircuit<G: Group> {
+  num_elts_per_step: usize,
+  x_i: Vec<G::Scalar>,
+}
+
+impl<G: Group> HashChainCircuit<G> {
+  // produces a preimage to be hashed
+  fn new(num_elts_per_step: usize) -> Self {
+    let mut rng = rand::thread_rng();
+    let x_i = (0..num_elts_per_step)
+      .map(|_| G::Scalar::random(&mut rng))
+      .collect::<Vec<_>>();
+
+    Self {
+      num_elts_per_step,
+      x_i,
+    }
+  }
+}
+
+impl<G: Group> StepCircuit<G::Scalar> for HashChainCircuit<G> {
+  fn arity(&self) -> usize {
+    1
+  }
+
+  fn synthesize<CS: ConstraintSystem<G::Scalar>>(
+    &self,
+    cs: &mut CS,
+    z_in: &[AllocatedNum<G::Scalar>],
+  ) -> Result<Vec<AllocatedNum<G::Scalar>>, SynthesisError> {
+    // z_in provides the running digest
+    assert_eq!(z_in.len(), 1);
+
+    // allocate x_i
+    let x_i = (0..self.num_elts_per_step)
+      .map(|i| AllocatedNum::alloc(cs.namespace(|| format!("x_{}", i)), || Ok(self.x_i[i])))
+      .collect::<Result<Vec<_>, _>>()?;
+
+    // concatenate z_in and x_i
+    let mut m = z_in.to_vec();
+    m.extend(x_i);
+
+    let elt = m
+      .iter()
+      .map(|x| Elt::Allocated(x.clone()))
+      .collect::<Vec<_>>();
+
+    let num_absorbs = 1 + self.num_elts_per_step as u32;
+
+    let parameter = IOPattern(vec![SpongeOp::Absorb(num_absorbs), SpongeOp::Squeeze(1u32)]);
+
+    let pc = Sponge::<G::Scalar, U24>::api_constants(Strength::Standard);
+    let mut ns = cs.namespace(|| "ns");
+
+    let z_out = {
+      let mut sponge = SpongeCircuit::new_with_constants(&pc, Simplex);
+      let acc = &mut ns;
+
+      sponge.start(parameter, None, acc);
+      neptune::sponge::api::SpongeAPI::absorb(&mut sponge, num_absorbs, &elt, acc);
+
+      let output = neptune::sponge::api::SpongeAPI::squeeze(&mut sponge, 1, acc);
+      sponge.finish(acc).unwrap();
+      Elt::ensure_allocated(&output[0], &mut ns.namespace(|| "ensure allocated"), true)?
+    };
+
+    Ok(vec![z_out])
+  }
+}
+
+/// cargo run --release --example and
+fn main() {
+  println!("=========================================================");
+  println!("Nova-based hashchain example");
+  println!("=========================================================");
+
+  let num_steps = 10;
+  for num_elts_per_step in [1024, 2048, 4096] {
+    // number of instances of AND per Nova's recursive step
+    let circuit_primary = HashChainCircuit::new(num_elts_per_step);
+    let circuit_secondary = TrivialCircuit::default();
+
+    // produce public parameters
+    let start = Instant::now();
+    println!("Producing public parameters...");
+    let pp = PublicParams::<
+      E1,
+      E2,
+      HashChainCircuit<<E1 as Engine>::GE>,
+      TrivialCircuit<<E2 as Engine>::Scalar>,
+    >::setup(
+      &circuit_primary,
+      &circuit_secondary,
+      &*S1::ck_floor(),
+      &*S2::ck_floor(),
+    )
+    .unwrap();
+    println!("PublicParams::setup, took {:?} ", start.elapsed());
+
+    println!(
+      "Number of constraints per step (primary circuit): {}",
+      pp.num_constraints().0
+    );
+    println!(
+      "Number of constraints per step (secondary circuit): {}",
+      pp.num_constraints().1
+    );
+
+    println!(
+      "Number of variables per step (primary circuit): {}",
+      pp.num_variables().0
+    );
+    println!(
+      "Number of variables per step (secondary circuit): {}",
+      pp.num_variables().1
+    );
+
+    // produce non-deterministic advice
+    let circuits = (0..num_steps)
+      .map(|_| HashChainCircuit::new(num_elts_per_step))
+      .collect::<Vec<_>>();
+
+    type C1 = HashChainCircuit<<E1 as Engine>::GE>;
+    type C2 = TrivialCircuit<<E2 as Engine>::Scalar>;
+
+    // produce a recursive SNARK
+    println!(
+      "Generating a RecursiveSNARK with {num_elts_per_step} field elements per hashchain node..."
+    );
+    let mut recursive_snark: RecursiveSNARK<E1, E2, C1, C2> =
+      RecursiveSNARK::<E1, E2, C1, C2>::new(
+        &pp,
+        &circuits[0],
+        &circuit_secondary,
+        &[<E1 as Engine>::Scalar::zero()],
+        &[<E2 as Engine>::Scalar::zero()],
+      )
+      .unwrap();
+
+    for (i, circuit_primary) in circuits.iter().enumerate() {
+      let start = Instant::now();
+      let res = recursive_snark.prove_step(&pp, circuit_primary, &circuit_secondary);
+      assert!(res.is_ok());
+
+      println!("RecursiveSNARK::prove {} : took {:?} ", i, start.elapsed());
+    }
+
+    // verify the recursive SNARK
+    println!("Verifying a RecursiveSNARK...");
+    let res = recursive_snark.verify(
+      &pp,
+      num_steps,
+      &[<E1 as Engine>::Scalar::ZERO],
+      &[<E2 as Engine>::Scalar::ZERO],
+    );
+    println!("RecursiveSNARK::verify: {:?}", res.is_ok(),);
+    assert!(res.is_ok());
+
+    // produce a compressed SNARK
+    println!("Generating a CompressedSNARK using Spartan with HyperKZG...");
+    let (pk, vk) = CompressedSNARK::<_, _, _, _, S1, S2>::setup(&pp).unwrap();
+
+    let start = Instant::now();
+
+    let res = CompressedSNARK::<_, _, _, _, S1, S2>::prove(&pp, &pk, &recursive_snark);
+    println!(
+      "CompressedSNARK::prove: {:?}, took {:?}",
+      res.is_ok(),
+      start.elapsed()
+    );
+    assert!(res.is_ok());
+    let compressed_snark = res.unwrap();
+
+    let mut encoder = ZlibEncoder::new(Vec::new(), Compression::default());
+    bincode::serialize_into(&mut encoder, &compressed_snark).unwrap();
+    let compressed_snark_encoded = encoder.finish().unwrap();
+    println!(
+      "CompressedSNARK::len {:?} bytes",
+      compressed_snark_encoded.len()
+    );
+
+    // verify the compressed SNARK
+    println!("Verifying a CompressedSNARK...");
+    let start = Instant::now();
+    let res = compressed_snark.verify(
+      &vk,
+      num_steps,
+      &[<E1 as Engine>::Scalar::ZERO],
+      &[<E2 as Engine>::Scalar::ZERO],
+    );
+    println!(
+      "CompressedSNARK::verify: {:?}, took {:?}",
+      res.is_ok(),
+      start.elapsed()
+    );
+    assert!(res.is_ok());
+    println!("=========================================================");
+  }
+}